ANALISIS MODEL PREDIKSI FINANCIAL DISTRESS PERUSAHAAN BANK KONVENSIONAL MELALUI KOMPONEN RGEC

Abstract

Banking companies are engaged in the financial sector which tend to pose a high risk in their operational activities than other companies in different sectors. If the risks arising from the operational activities of bank companies are not managed properly, then this can lead to bank failure problems that can threaten the country's monetary stability. In this paper, the authors aim to formulate a financial distress prediction model to identifying and predicting conventional bank companies that will experience financial distress problems. To achieve this goal, the authors use the discriminant analysis method by using 8 independent variables that represent each RGEC component such as NPL, Cash Ratio, Managerial Ownership, Institutional Ownership, Proportion of Independent Commissioners, ROA, NIM and CAR to the financial distress as the dependent variable with a nominal scale. Based on the test results, the authors found that there were 4 independent variables that were able to predict financial distress like NPL, Cash Ratio, ROA and NIM with an accuracy of 95.83%, where this value met the validation requirements in discriminant analysis and could be used to predict financial distress in other conventional bank companies.